{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "4av2zQXS69d8"
   },
   "source": [
    "# Hudson and Thames' Minimum Spanning Tree Challenge\n",
    "Submission by @changchuanhong\n",
    "\n",
    "\n",
    "# Introduction\n",
    "This notebook submission would demonstrate my implementation of Krustal's algorithm with 50 randomly selected SP500 stock close data.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 54
    },
    "colab_type": "code",
    "id": "l-W_A6jF64bX",
    "outputId": "622b3421-c0ed-46d3-d64c-73ce3210dad6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List of tickers selected: ['GPS', 'KHC', 'SYK', 'HPE', 'IFF', 'WMB', 'ALGN', 'BR', 'NWS', 'ICE', 'ABC', 'NBL', 'WHR', 'JBHT', 'DUK', 'RMD', 'HRL', 'CHTR', 'PLD', 'CE', 'JCI', 'RTX', 'AXP', 'CHD', 'MLM', 'COF', 'MXIM', 'HAL', 'HPQ', 'XLNX', 'ZION', 'PVH', 'BSX', 'WFC', 'PRU', 'IPG', 'HUM', 'PFG', 'REG', 'MAA', 'IBM', 'AMAT', 'HAS', 'PM', 'NKE', 'CVX', 'AIZ', 'BWA', 'ETFC', 'ULTA']\n"
     ]
    }
   ],
   "source": [
    "# Randomly select 50 stock tickers from the SPX index.\n",
    "\n",
    "import utils\n",
    "import KrustalMST\n",
    "import unittests\n",
    "import yfinance as yf\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "sample = utils.getSPXTickers(count = 50)\n",
    "\n",
    "print('List of tickers selected: {}'.format(sample))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 383
    },
    "colab_type": "code",
    "id": "WKiecG9r8QlQ",
    "outputId": "f7af5737-167c-4306-8c13-6c2e776b03e3"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GPS</th>\n",
       "      <th>KHC</th>\n",
       "      <th>SYK</th>\n",
       "      <th>HPE</th>\n",
       "      <th>IFF</th>\n",
       "      <th>WMB</th>\n",
       "      <th>ALGN</th>\n",
       "      <th>BR</th>\n",
       "      <th>NWS</th>\n",
       "      <th>ICE</th>\n",
       "      <th>ABC</th>\n",
       "      <th>NBL</th>\n",
       "      <th>WHR</th>\n",
       "      <th>JBHT</th>\n",
       "      <th>DUK</th>\n",
       "      <th>RMD</th>\n",
       "      <th>HRL</th>\n",
       "      <th>CHTR</th>\n",
       "      <th>PLD</th>\n",
       "      <th>CE</th>\n",
       "      <th>JCI</th>\n",
       "      <th>RTX</th>\n",
       "      <th>AXP</th>\n",
       "      <th>CHD</th>\n",
       "      <th>MLM</th>\n",
       "      <th>COF</th>\n",
       "      <th>MXIM</th>\n",
       "      <th>HAL</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>XLNX</th>\n",
       "      <th>ZION</th>\n",
       "      <th>PVH</th>\n",
       "      <th>BSX</th>\n",
       "      <th>WFC</th>\n",
       "      <th>PRU</th>\n",
       "      <th>IPG</th>\n",
       "      <th>HUM</th>\n",
       "      <th>PFG</th>\n",
       "      <th>REG</th>\n",
       "      <th>MAA</th>\n",
       "      <th>IBM</th>\n",
       "      <th>AMAT</th>\n",
       "      <th>HAS</th>\n",
       "      <th>PM</th>\n",
       "      <th>NKE</th>\n",
       "      <th>CVX</th>\n",
       "      <th>AIZ</th>\n",
       "      <th>BWA</th>\n",
       "      <th>ETFC</th>\n",
       "      <th>ULTA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-16 00:00:00</th>\n",
       "      <td>13.07</td>\n",
       "      <td>34.40</td>\n",
       "      <td>186.59</td>\n",
       "      <td>9.72</td>\n",
       "      <td>129.61</td>\n",
       "      <td>19.90</td>\n",
       "      <td>309.00</td>\n",
       "      <td>127.46</td>\n",
       "      <td>12.79</td>\n",
       "      <td>92.37</td>\n",
       "      <td>102.74</td>\n",
       "      <td>9.95</td>\n",
       "      <td>144.31</td>\n",
       "      <td>132.55</td>\n",
       "      <td>81.07</td>\n",
       "      <td>195.82</td>\n",
       "      <td>49.53</td>\n",
       "      <td>558.03</td>\n",
       "      <td>92.10</td>\n",
       "      <td>90.59</td>\n",
       "      <td>37.17</td>\n",
       "      <td>62.37</td>\n",
       "      <td>96.32</td>\n",
       "      <td>84.20</td>\n",
       "      <td>223.09</td>\n",
       "      <td>63.36</td>\n",
       "      <td>69.54</td>\n",
       "      <td>13.09</td>\n",
       "      <td>17.83</td>\n",
       "      <td>99.17</td>\n",
       "      <td>33.39</td>\n",
       "      <td>51.26</td>\n",
       "      <td>36.37</td>\n",
       "      <td>25.46</td>\n",
       "      <td>64.25</td>\n",
       "      <td>18.20</td>\n",
       "      <td>395.89</td>\n",
       "      <td>44.76</td>\n",
       "      <td>42.10</td>\n",
       "      <td>112.02</td>\n",
       "      <td>124.01</td>\n",
       "      <td>62.34</td>\n",
       "      <td>77.51</td>\n",
       "      <td>75.35</td>\n",
       "      <td>97.26</td>\n",
       "      <td>88.36</td>\n",
       "      <td>105.07</td>\n",
       "      <td>37.77</td>\n",
       "      <td>54.37</td>\n",
       "      <td>203.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-17 00:00:00</th>\n",
       "      <td>12.89</td>\n",
       "      <td>35.01</td>\n",
       "      <td>193.05</td>\n",
       "      <td>9.67</td>\n",
       "      <td>130.99</td>\n",
       "      <td>19.77</td>\n",
       "      <td>322.30</td>\n",
       "      <td>129.10</td>\n",
       "      <td>12.80</td>\n",
       "      <td>93.83</td>\n",
       "      <td>104.45</td>\n",
       "      <td>9.65</td>\n",
       "      <td>142.56</td>\n",
       "      <td>136.82</td>\n",
       "      <td>82.40</td>\n",
       "      <td>199.00</td>\n",
       "      <td>49.92</td>\n",
       "      <td>564.66</td>\n",
       "      <td>95.34</td>\n",
       "      <td>89.53</td>\n",
       "      <td>37.67</td>\n",
       "      <td>62.20</td>\n",
       "      <td>95.18</td>\n",
       "      <td>84.87</td>\n",
       "      <td>223.55</td>\n",
       "      <td>61.99</td>\n",
       "      <td>70.04</td>\n",
       "      <td>13.08</td>\n",
       "      <td>17.55</td>\n",
       "      <td>100.49</td>\n",
       "      <td>32.56</td>\n",
       "      <td>49.23</td>\n",
       "      <td>37.71</td>\n",
       "      <td>24.95</td>\n",
       "      <td>64.14</td>\n",
       "      <td>18.00</td>\n",
       "      <td>404.49</td>\n",
       "      <td>44.51</td>\n",
       "      <td>41.70</td>\n",
       "      <td>112.92</td>\n",
       "      <td>125.11</td>\n",
       "      <td>62.30</td>\n",
       "      <td>77.49</td>\n",
       "      <td>75.03</td>\n",
       "      <td>96.28</td>\n",
       "      <td>87.19</td>\n",
       "      <td>104.17</td>\n",
       "      <td>37.49</td>\n",
       "      <td>54.14</td>\n",
       "      <td>203.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-20 00:00:00</th>\n",
       "      <td>12.41</td>\n",
       "      <td>34.12</td>\n",
       "      <td>190.68</td>\n",
       "      <td>9.55</td>\n",
       "      <td>128.72</td>\n",
       "      <td>19.29</td>\n",
       "      <td>312.97</td>\n",
       "      <td>129.32</td>\n",
       "      <td>12.73</td>\n",
       "      <td>94.25</td>\n",
       "      <td>102.19</td>\n",
       "      <td>10.18</td>\n",
       "      <td>143.06</td>\n",
       "      <td>134.40</td>\n",
       "      <td>81.10</td>\n",
       "      <td>203.01</td>\n",
       "      <td>49.70</td>\n",
       "      <td>565.51</td>\n",
       "      <td>94.73</td>\n",
       "      <td>91.79</td>\n",
       "      <td>36.80</td>\n",
       "      <td>61.41</td>\n",
       "      <td>94.00</td>\n",
       "      <td>84.29</td>\n",
       "      <td>221.44</td>\n",
       "      <td>60.84</td>\n",
       "      <td>71.37</td>\n",
       "      <td>13.41</td>\n",
       "      <td>17.65</td>\n",
       "      <td>103.03</td>\n",
       "      <td>32.02</td>\n",
       "      <td>47.34</td>\n",
       "      <td>37.17</td>\n",
       "      <td>24.57</td>\n",
       "      <td>63.02</td>\n",
       "      <td>17.45</td>\n",
       "      <td>396.76</td>\n",
       "      <td>43.86</td>\n",
       "      <td>41.17</td>\n",
       "      <td>110.02</td>\n",
       "      <td>126.37</td>\n",
       "      <td>63.73</td>\n",
       "      <td>78.00</td>\n",
       "      <td>72.89</td>\n",
       "      <td>95.65</td>\n",
       "      <td>85.27</td>\n",
       "      <td>103.21</td>\n",
       "      <td>37.77</td>\n",
       "      <td>53.55</td>\n",
       "      <td>200.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-21 00:00:00</th>\n",
       "      <td>12.77</td>\n",
       "      <td>34.53</td>\n",
       "      <td>192.51</td>\n",
       "      <td>9.66</td>\n",
       "      <td>127.94</td>\n",
       "      <td>20.11</td>\n",
       "      <td>315.33</td>\n",
       "      <td>129.95</td>\n",
       "      <td>12.76</td>\n",
       "      <td>95.11</td>\n",
       "      <td>104.15</td>\n",
       "      <td>10.97</td>\n",
       "      <td>143.76</td>\n",
       "      <td>133.03</td>\n",
       "      <td>82.33</td>\n",
       "      <td>204.40</td>\n",
       "      <td>49.75</td>\n",
       "      <td>564.68</td>\n",
       "      <td>97.93</td>\n",
       "      <td>93.63</td>\n",
       "      <td>36.71</td>\n",
       "      <td>63.05</td>\n",
       "      <td>96.33</td>\n",
       "      <td>84.50</td>\n",
       "      <td>225.69</td>\n",
       "      <td>62.87</td>\n",
       "      <td>69.00</td>\n",
       "      <td>14.32</td>\n",
       "      <td>17.48</td>\n",
       "      <td>102.15</td>\n",
       "      <td>33.74</td>\n",
       "      <td>49.02</td>\n",
       "      <td>37.48</td>\n",
       "      <td>26.20</td>\n",
       "      <td>64.99</td>\n",
       "      <td>17.68</td>\n",
       "      <td>397.59</td>\n",
       "      <td>44.80</td>\n",
       "      <td>40.58</td>\n",
       "      <td>109.36</td>\n",
       "      <td>126.06</td>\n",
       "      <td>63.81</td>\n",
       "      <td>78.83</td>\n",
       "      <td>75.92</td>\n",
       "      <td>98.36</td>\n",
       "      <td>91.39</td>\n",
       "      <td>104.70</td>\n",
       "      <td>37.70</td>\n",
       "      <td>54.08</td>\n",
       "      <td>201.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-22 00:00:00</th>\n",
       "      <td>12.54</td>\n",
       "      <td>34.56</td>\n",
       "      <td>193.80</td>\n",
       "      <td>9.69</td>\n",
       "      <td>129.35</td>\n",
       "      <td>19.39</td>\n",
       "      <td>316.06</td>\n",
       "      <td>130.61</td>\n",
       "      <td>12.87</td>\n",
       "      <td>95.17</td>\n",
       "      <td>102.95</td>\n",
       "      <td>10.71</td>\n",
       "      <td>147.79</td>\n",
       "      <td>134.49</td>\n",
       "      <td>82.13</td>\n",
       "      <td>205.46</td>\n",
       "      <td>49.15</td>\n",
       "      <td>564.22</td>\n",
       "      <td>98.61</td>\n",
       "      <td>93.55</td>\n",
       "      <td>36.85</td>\n",
       "      <td>62.75</td>\n",
       "      <td>96.74</td>\n",
       "      <td>84.01</td>\n",
       "      <td>227.21</td>\n",
       "      <td>63.57</td>\n",
       "      <td>69.39</td>\n",
       "      <td>14.21</td>\n",
       "      <td>17.60</td>\n",
       "      <td>103.49</td>\n",
       "      <td>33.30</td>\n",
       "      <td>49.29</td>\n",
       "      <td>38.34</td>\n",
       "      <td>25.95</td>\n",
       "      <td>64.85</td>\n",
       "      <td>17.74</td>\n",
       "      <td>396.93</td>\n",
       "      <td>44.84</td>\n",
       "      <td>40.88</td>\n",
       "      <td>110.66</td>\n",
       "      <td>128.76</td>\n",
       "      <td>64.39</td>\n",
       "      <td>79.25</td>\n",
       "      <td>74.27</td>\n",
       "      <td>98.64</td>\n",
       "      <td>89.56</td>\n",
       "      <td>105.19</td>\n",
       "      <td>38.12</td>\n",
       "      <td>53.76</td>\n",
       "      <td>203.78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       GPS    KHC     SYK   HPE  ...     AIZ    BWA   ETFC    ULTA\n",
       "2020-07-16 00:00:00  13.07  34.40  186.59  9.72  ...  105.07  37.77  54.37  203.18\n",
       "2020-07-17 00:00:00  12.89  35.01  193.05  9.67  ...  104.17  37.49  54.14  203.00\n",
       "2020-07-20 00:00:00  12.41  34.12  190.68  9.55  ...  103.21  37.77  53.55  200.06\n",
       "2020-07-21 00:00:00  12.77  34.53  192.51  9.66  ...  104.70  37.70  54.08  201.96\n",
       "2020-07-22 00:00:00  12.54  34.56  193.80  9.69  ...  105.19  38.12  53.76  203.78\n",
       "\n",
       "[5 rows x 50 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retrieve the closing prices of the selected stocks.\n",
    "\n",
    "close = pd.DataFrame()\n",
    "for i in sample:\n",
    "    current_ticker = yf.Ticker(i)\n",
    "    close = pd.concat([close, current_ticker.history(period = 'max')['Close'].dropna()], axis = 1)\n",
    "\n",
    "close.columns = sample\n",
    "close.tail(5) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Qqih9Sy0yjR4"
   },
   "source": [
    "### Compute the distance matrix\n",
    "\n",
    "The distance metrix is implemented as described by the paper referenced in the challenge. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 266
    },
    "colab_type": "code",
    "id": "GBkrqRfHZx38",
    "outputId": "d92df8c9-983b-481c-cd8c-9bf9fb006e21"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance Matrix of dimension (50, 50) generated\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:2: RuntimeWarning: divide by zero encountered in log10\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GPS</th>\n",
       "      <th>KHC</th>\n",
       "      <th>SYK</th>\n",
       "      <th>HPE</th>\n",
       "      <th>IFF</th>\n",
       "      <th>WMB</th>\n",
       "      <th>ALGN</th>\n",
       "      <th>BR</th>\n",
       "      <th>NWS</th>\n",
       "      <th>ICE</th>\n",
       "      <th>ABC</th>\n",
       "      <th>NBL</th>\n",
       "      <th>WHR</th>\n",
       "      <th>JBHT</th>\n",
       "      <th>DUK</th>\n",
       "      <th>RMD</th>\n",
       "      <th>HRL</th>\n",
       "      <th>CHTR</th>\n",
       "      <th>PLD</th>\n",
       "      <th>CE</th>\n",
       "      <th>JCI</th>\n",
       "      <th>RTX</th>\n",
       "      <th>AXP</th>\n",
       "      <th>CHD</th>\n",
       "      <th>MLM</th>\n",
       "      <th>COF</th>\n",
       "      <th>MXIM</th>\n",
       "      <th>HAL</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>XLNX</th>\n",
       "      <th>ZION</th>\n",
       "      <th>PVH</th>\n",
       "      <th>BSX</th>\n",
       "      <th>WFC</th>\n",
       "      <th>PRU</th>\n",
       "      <th>IPG</th>\n",
       "      <th>HUM</th>\n",
       "      <th>PFG</th>\n",
       "      <th>REG</th>\n",
       "      <th>MAA</th>\n",
       "      <th>IBM</th>\n",
       "      <th>AMAT</th>\n",
       "      <th>HAS</th>\n",
       "      <th>PM</th>\n",
       "      <th>NKE</th>\n",
       "      <th>CVX</th>\n",
       "      <th>AIZ</th>\n",
       "      <th>BWA</th>\n",
       "      <th>ETFC</th>\n",
       "      <th>ULTA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GPS</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.239796</td>\n",
       "      <td>1.266677</td>\n",
       "      <td>1.063069</td>\n",
       "      <td>1.231160</td>\n",
       "      <td>1.304376</td>\n",
       "      <td>1.252741</td>\n",
       "      <td>1.151414</td>\n",
       "      <td>1.097728</td>\n",
       "      <td>1.184746</td>\n",
       "      <td>1.278147</td>\n",
       "      <td>1.265879</td>\n",
       "      <td>1.194457</td>\n",
       "      <td>1.231863</td>\n",
       "      <td>1.276237</td>\n",
       "      <td>1.285844</td>\n",
       "      <td>1.343954</td>\n",
       "      <td>1.246253</td>\n",
       "      <td>1.177863</td>\n",
       "      <td>1.119922</td>\n",
       "      <td>1.213487</td>\n",
       "      <td>1.171010</td>\n",
       "      <td>1.160586</td>\n",
       "      <td>1.360214</td>\n",
       "      <td>1.180188</td>\n",
       "      <td>1.133554</td>\n",
       "      <td>1.253471</td>\n",
       "      <td>1.253381</td>\n",
       "      <td>1.240812</td>\n",
       "      <td>1.240105</td>\n",
       "      <td>1.266704</td>\n",
       "      <td>1.186504</td>\n",
       "      <td>1.243987</td>\n",
       "      <td>1.257486</td>\n",
       "      <td>1.073752</td>\n",
       "      <td>1.217263</td>\n",
       "      <td>1.302580</td>\n",
       "      <td>1.085690</td>\n",
       "      <td>1.169545</td>\n",
       "      <td>1.197448</td>\n",
       "      <td>1.231986</td>\n",
       "      <td>1.246663</td>\n",
       "      <td>1.234153</td>\n",
       "      <td>1.151657</td>\n",
       "      <td>1.244593</td>\n",
       "      <td>1.231409</td>\n",
       "      <td>1.126476</td>\n",
       "      <td>1.157439</td>\n",
       "      <td>1.218394</td>\n",
       "      <td>1.140828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KHC</th>\n",
       "      <td>1.239796</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.114407</td>\n",
       "      <td>1.148214</td>\n",
       "      <td>1.094590</td>\n",
       "      <td>1.209372</td>\n",
       "      <td>1.183600</td>\n",
       "      <td>1.146327</td>\n",
       "      <td>1.160607</td>\n",
       "      <td>1.139260</td>\n",
       "      <td>1.167476</td>\n",
       "      <td>1.212083</td>\n",
       "      <td>1.119859</td>\n",
       "      <td>1.116234</td>\n",
       "      <td>1.086999</td>\n",
       "      <td>1.194861</td>\n",
       "      <td>1.124106</td>\n",
       "      <td>1.181767</td>\n",
       "      <td>1.050350</td>\n",
       "      <td>1.147799</td>\n",
       "      <td>1.109725</td>\n",
       "      <td>1.157738</td>\n",
       "      <td>1.118732</td>\n",
       "      <td>1.156318</td>\n",
       "      <td>1.203300</td>\n",
       "      <td>1.117153</td>\n",
       "      <td>1.142124</td>\n",
       "      <td>1.151429</td>\n",
       "      <td>1.197478</td>\n",
       "      <td>1.175538</td>\n",
       "      <td>1.174953</td>\n",
       "      <td>1.142896</td>\n",
       "      <td>1.145488</td>\n",
       "      <td>1.081563</td>\n",
       "      <td>1.055824</td>\n",
       "      <td>1.095257</td>\n",
       "      <td>1.183773</td>\n",
       "      <td>1.087244</td>\n",
       "      <td>1.141580</td>\n",
       "      <td>1.106534</td>\n",
       "      <td>1.082513</td>\n",
       "      <td>1.138469</td>\n",
       "      <td>1.196498</td>\n",
       "      <td>1.068918</td>\n",
       "      <td>1.145719</td>\n",
       "      <td>1.117527</td>\n",
       "      <td>1.163703</td>\n",
       "      <td>1.174652</td>\n",
       "      <td>1.106990</td>\n",
       "      <td>1.244013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SYK</th>\n",
       "      <td>1.266677</td>\n",
       "      <td>1.114407</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.002514</td>\n",
       "      <td>1.221168</td>\n",
       "      <td>1.328291</td>\n",
       "      <td>1.194917</td>\n",
       "      <td>1.023650</td>\n",
       "      <td>1.056205</td>\n",
       "      <td>1.097191</td>\n",
       "      <td>1.219089</td>\n",
       "      <td>1.261789</td>\n",
       "      <td>1.230329</td>\n",
       "      <td>1.249904</td>\n",
       "      <td>1.264847</td>\n",
       "      <td>1.226980</td>\n",
       "      <td>1.323115</td>\n",
       "      <td>1.130763</td>\n",
       "      <td>1.160213</td>\n",
       "      <td>1.061827</td>\n",
       "      <td>1.239655</td>\n",
       "      <td>1.191113</td>\n",
       "      <td>1.200217</td>\n",
       "      <td>1.349014</td>\n",
       "      <td>1.182964</td>\n",
       "      <td>1.173982</td>\n",
       "      <td>1.245858</td>\n",
       "      <td>1.251920</td>\n",
       "      <td>1.267065</td>\n",
       "      <td>1.237653</td>\n",
       "      <td>1.250341</td>\n",
       "      <td>1.254540</td>\n",
       "      <td>1.165488</td>\n",
       "      <td>1.258533</td>\n",
       "      <td>1.035832</td>\n",
       "      <td>1.254685</td>\n",
       "      <td>1.253107</td>\n",
       "      <td>1.040572</td>\n",
       "      <td>1.170635</td>\n",
       "      <td>1.180448</td>\n",
       "      <td>1.256409</td>\n",
       "      <td>1.253769</td>\n",
       "      <td>1.309760</td>\n",
       "      <td>1.037039</td>\n",
       "      <td>1.278367</td>\n",
       "      <td>1.244308</td>\n",
       "      <td>1.099202</td>\n",
       "      <td>1.178585</td>\n",
       "      <td>1.232020</td>\n",
       "      <td>1.134141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HPE</th>\n",
       "      <td>1.063069</td>\n",
       "      <td>1.148214</td>\n",
       "      <td>1.002514</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.073172</td>\n",
       "      <td>1.110994</td>\n",
       "      <td>1.068601</td>\n",
       "      <td>1.094125</td>\n",
       "      <td>1.013137</td>\n",
       "      <td>1.076650</td>\n",
       "      <td>1.149955</td>\n",
       "      <td>1.049596</td>\n",
       "      <td>1.020379</td>\n",
       "      <td>1.049048</td>\n",
       "      <td>1.191128</td>\n",
       "      <td>1.181769</td>\n",
       "      <td>1.269529</td>\n",
       "      <td>1.155211</td>\n",
       "      <td>1.081172</td>\n",
       "      <td>0.949831</td>\n",
       "      <td>1.026061</td>\n",
       "      <td>0.956510</td>\n",
       "      <td>0.965652</td>\n",
       "      <td>1.267991</td>\n",
       "      <td>1.081222</td>\n",
       "      <td>0.916412</td>\n",
       "      <td>1.003843</td>\n",
       "      <td>1.027494</td>\n",
       "      <td>0.920888</td>\n",
       "      <td>1.043276</td>\n",
       "      <td>0.942962</td>\n",
       "      <td>0.986624</td>\n",
       "      <td>1.044093</td>\n",
       "      <td>0.949632</td>\n",
       "      <td>0.862987</td>\n",
       "      <td>0.986682</td>\n",
       "      <td>1.125464</td>\n",
       "      <td>0.872328</td>\n",
       "      <td>1.094091</td>\n",
       "      <td>1.131459</td>\n",
       "      <td>0.946087</td>\n",
       "      <td>0.986297</td>\n",
       "      <td>1.093438</td>\n",
       "      <td>1.134017</td>\n",
       "      <td>1.003596</td>\n",
       "      <td>1.011269</td>\n",
       "      <td>1.079396</td>\n",
       "      <td>0.989391</td>\n",
       "      <td>0.948777</td>\n",
       "      <td>1.124139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IFF</th>\n",
       "      <td>1.231160</td>\n",
       "      <td>1.094590</td>\n",
       "      <td>1.221168</td>\n",
       "      <td>1.073172</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.296168</td>\n",
       "      <td>1.214043</td>\n",
       "      <td>1.058404</td>\n",
       "      <td>1.081147</td>\n",
       "      <td>1.115406</td>\n",
       "      <td>1.224955</td>\n",
       "      <td>1.223493</td>\n",
       "      <td>1.171529</td>\n",
       "      <td>1.212037</td>\n",
       "      <td>1.192663</td>\n",
       "      <td>1.259131</td>\n",
       "      <td>1.281774</td>\n",
       "      <td>1.157885</td>\n",
       "      <td>1.097763</td>\n",
       "      <td>0.990021</td>\n",
       "      <td>1.206409</td>\n",
       "      <td>1.135188</td>\n",
       "      <td>1.133003</td>\n",
       "      <td>1.324490</td>\n",
       "      <td>1.129722</td>\n",
       "      <td>1.144736</td>\n",
       "      <td>1.240305</td>\n",
       "      <td>1.194854</td>\n",
       "      <td>1.263135</td>\n",
       "      <td>1.240581</td>\n",
       "      <td>1.222506</td>\n",
       "      <td>1.217513</td>\n",
       "      <td>1.215362</td>\n",
       "      <td>1.219691</td>\n",
       "      <td>1.010611</td>\n",
       "      <td>1.199169</td>\n",
       "      <td>1.244872</td>\n",
       "      <td>1.021535</td>\n",
       "      <td>1.137714</td>\n",
       "      <td>1.136583</td>\n",
       "      <td>1.177517</td>\n",
       "      <td>1.235323</td>\n",
       "      <td>1.285515</td>\n",
       "      <td>1.061378</td>\n",
       "      <td>1.272863</td>\n",
       "      <td>1.201539</td>\n",
       "      <td>1.038395</td>\n",
       "      <td>1.120169</td>\n",
       "      <td>1.218063</td>\n",
       "      <td>1.158548</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          GPS       KHC       SYK  ...       BWA      ETFC      ULTA\n",
       "GPS  0.000000  1.239796  1.266677  ...  1.157439  1.218394  1.140828\n",
       "KHC  1.239796  0.000000  1.114407  ...  1.174652  1.106990  1.244013\n",
       "SYK  1.266677  1.114407  0.000000  ...  1.178585  1.232020  1.134141\n",
       "HPE  1.063069  1.148214  1.002514  ...  0.989391  0.948777  1.124139\n",
       "IFF  1.231160  1.094590  1.221168  ...  1.120169  1.218063  1.158548\n",
       "\n",
       "[5 rows x 50 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute the distance matrix with the methodology provided in the paper\n",
    "close_returns = np.log10(close) - np.log10(close).shift(1)\n",
    "distance_matrix = np.sqrt(2*(1 - close_returns.corr(method ='pearson')))\n",
    "print('Distance Matrix of dimension {} generated'.format(distance_matrix.shape))\n",
    "\n",
    "# Data sanity check\n",
    "if distance_matrix.isnull().values.any():\n",
    "    print('There might be bad tickers or that yFinance has not retrieved the required data correctly.')\n",
    "distance_matrix.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "OFPPBHXzzCyQ"
   },
   "source": [
    "### Compute the Adjacency Matrix\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "HBoUaCiPzB_y"
   },
   "outputs": [],
   "source": [
    "mst = KrustalMST.MST(distance_matrix)\n",
    "adjacency_matrix = mst.buildMST()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "XQJ54O0Map4J"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('collected_courses.csv')\n",
    "df = df[df['Prerequisite'].str.contains(' OR', case = True, regex = False).notnull()]\n",
    "df = df[df['Prerequisite'].str.contains(' OR', case = True, regex = False)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "dvbefUAq33Cc"
   },
   "source": [
    "# Visualization of the data\n",
    "\n",
    "### Plot of the Minimum Spanning Tree\n",
    "\n",
    "There are several distinct clusters found by the MST algorithm. For example, Prudential, Zions Bancorporation and Wells Fargo are closely interlinked which is to be expected since these are financial companies.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "AYIOHCAr66GB",
    "outputId": "932b6971-6ae5-49f5-aa0d-8552264199b6"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "\n",
    "plt.figure(num=None, figsize=(25, 25), dpi=80, facecolor='w', edgecolor='k')\n",
    "\n",
    "df = pd.DataFrame(adjacency_matrix, columns = distance_matrix.columns, index = distance_matrix.columns)\n",
    "G = nx.from_pandas_adjacency(df, create_using=nx.DiGraph)\n",
    "nx.draw_networkx(G, node_size=500)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "LBHbxF4T6O9-"
   },
   "source": [
    "### Visualize how each cluster is composed\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 385
    },
    "colab_type": "code",
    "id": "AgjV_tdd32vz",
    "outputId": "ef3e8d55-2fe8-4a72-d44e-4cedbcda52a0"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "\n",
    "linkage_matrix = linkage(distance_matrix, \"single\")\n",
    "plt.figure(figsize=(20, 5))\n",
    "dendrogram(linkage_matrix, labels=distance_matrix.columns)\n",
    "plt.title(\"Dendogram of selected tickers\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "94ytltbE6gzq"
   },
   "source": [
    "# Conclusion\n",
    "\n",
    "In this notebook, I demonstrate the implementation of a minimum spanning tree to cluster stocks according to their historical correlations. However, the clusters formed with this method might be unstable; other forms of clustering may be explored as part of future research.\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Untitled2.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
